Design of User Privacy Information Protection System in Big Data Network Environment

With the continuous advancement of the new technological revolution and industrial transformation, big data technology has become a new driving force supporting the harmonious and stable development of society. In addition, the explosive development of information technology has made the importance of data as a factor of production increasingly prominent, and the status of data security is constantly improving. Strengthening data security governance, protecting the privacy of personal information, and even ensuring national information security, are of great significance. In fact, user privacy breaches often occur in big data network environments, and user privacy may be compromised in various aspects such as data collection, storage, mining, and sharing. This article analyzes the relevant connotations and characteristics of big data environment and privacy information, and designs a privacy information protection system based on big data analysis. The system uses Kubernetes cluster technology as the core, providing infrastructure support for system functions. On this basis, the big data processing layer transfers information through file transfer protocols to the information protection layer. This layer is based on the TBS architecture and introduces the MapReduce programming model, Parallel storage of massive amounts of information, and a privacy information protection model based on attribute classification, thereby achieving protection of privacy information. This system can achieve parallel storage of massive amounts of information, with low risk of privacy information leakage. It ensures the privacy of information presentation while not compromising the availability of information after privacy protection.